R&D Engineer

This hybrid remote position is based in Houma, Louisiana, with an annual salary range of $85,000 to $110,000. As an R&D Engineer at Fluence Labs, you will advance reconstruction and analysis algorithms for X-ray CT imaging systems while providing essential IT support across the organization. The role emphasizes computational imaging, collaboration with both technical and non-technical teams, and the maintenance of imaging pipelines and data systems.

Responsibilities

• Develop, optimize, and refine reconstruction algorithms for X-ray CT and other advanced non-destructive testing imaging modalities.
• Build physics-based and data-driven pipelines to improve image quality, processing speed, reliability, and automation.
• Leverage machine learning and deep learning techniques to enhance reconstructions, reduce artifacts, and improve overall image quality.
• Tackle complex inverse problems using modern numerical optimization strategies.
• Write high-performance software with GPU acceleration via CUDA and employ parallel computing approaches.
• Handle and analyze large 3D volumetric datasets.
• Prototype innovative ideas and transition them into production software for NDT applications.
• Plan and execute simulation studies alongside real-world experimental validation.
• Collaborate closely with hardware, software, applications, and inspection teams.
• Document algorithms, test results, and code with clear, thorough records.
• Support internal innovation efforts, contribute to technical reports, and assist with external presentations as needed.
• Provide day-to-day IT support, troubleshooting hardware, software, and network issues affecting imaging workstations and data systems.
• Maintain, update, and optimize CT reconstruction tools, GPU environments, data pipelines, and related software.
• Assist with setup and basic support for high-performance computing systems, laptops, servers, and peripherals.
• Support routine data backups, secure file sharing, and fundamental data protection practices.
• Coordinate with external IT resources when more advanced issues arise.

Requirements

• Solid technical proficiency in computational imaging concepts and techniques.
• Ability to collaborate effectively with both technical and non-technical stakeholders across teams.

Technologies

• CUDA